Impact of peripheral lymphocyte subsets on prognosis for patients after acute ischemic stroke: A potential disease prediction model approach

Abstract Aims To investigate the relationship between peripheral blood lymphocyte subsets and prognosis in patients with acute ischemic stroke (AIS). Methods We enrolled 294 patients with AIS and collected peripheral blood samples for analysis of lymphocyte subsets. Prognosis was assessed at 3 months using the modified Rankin Scale (mRS). Association between lymphocyte count and poor outcomes (mRS score >2) was assessed using logistic regression. Individualized prediction models were developed to predict poor outcomes. Results Patients in the mRS score ≤2 group had higher T‐cell percentage (odds ratio [OR] = 0.947; 95% confidence interval [CI]: 0.899–0.998; p = 0.040), CD3+ T‐cell count (OR = 0.999; 95% CI: 0.998–1.000; p = 0.018), and CD4+ T‐cell count (OR = 0.998; 95% CI: 0.997–1.000; p = 0.030) than those in the mRS score >2 group 1–3 days after stroke. The prediction model for poor prognosis based on the CD4+ T‐cell count showed good discrimination (area under the curve of 0.844), calibration (p > 0.05), and clinical utility. Conclusion Lower T cell percentage, CD3+, and CD4+ T‐cell counts 1–3 days after stroke were independently associated with increased risk of poor prognosis. Individualized predictive model of poor prognosis based on CD4+ T‐cell count have good accuracy and may predict disease prognosis.

methods capable of determining early-stage prognosis.Hence, the identification of reliable biomarkers for early prognostic prediction in acute stroke is imperative to enhance patient care and outcomes.
Mounting evidence underscores the essential involvement of immune mechanisms in ischemic stroke. 4Bidirectional communication between neuroinflammation and the peripheral immune system is robust throughout the course of CNS damage induced by ischemic stroke.In ischemic stroke, hypoxia in the brain tissue at the injury site initiates autoimmunity against CNS antigens.This induces intrinsic immune cells, including astrocytes and microglia, to release significant levels of proinflammatory cytokines, such as interleukin (IL)-1β, IL-6, interferon (IFN)γ, and tumor necrosis factor (TNF)α.
These cytokines then stimulate peripheral immune cells such as neutrophils, monocytes, and T and B cells to cross the damaged blood-brain barrier and infiltrate the brain parenchyma, thereby intensifying neuroinflammation. 5,6[9] Lymphocytes are key to both innate and adaptive immune responses.Specifically, their role in neuroinflammation is predominantly associated with T cells, which are classified based on surface markers as CD4 + (helper/inducer T, Th) cells and CD8 + (suppressor/ cytotoxic T, Ts) cells. 102][13] It not only releases proinflammatory factors but also secretes protective anti-inflammatory factors.
Thus, the dual nature of lymphocytes makes them pivotal in the injury, repair, and survival of ischemic brain tissue following a stroke. 14sed on existing reports, we hypothesized that T cells and their products could offer a potential intervention for neuronal protection against stroke injury. 15Consequently, our objective was to investigate the link between peripheral blood lymphocyte subset counts and proportions and the prognosis in patients with varying infarction durations.Furthermore, we aimed to ascertain the potential prognostic utility of disease prediction models for patients with AIS.

TA B L E 2
All tests were two-sided, with statistical significance defined as p < 0.05.

| Baseline characteristics of the patients
This study initially enrolled 354 patients with AIS based on the specified inclusion criteria, with 294 patients included in the final analysis.Detailed baseline clinical features of the patients are listed in Table 1.
Compared to patients in the mRS score ≤2 group, patients in the mRS score >2 group were older (median 61 versus 66 years, p = 0.001), had a lower proportion of males (75.3% versus 54.5%, p = 0.002), and had a higher proportion of patients with previous stroke (20.9% versus 36.4%,p = 0.015).In addition, homocysteine (median 13.0 versus 14.6 μmol/L, p = 0.006), HDL cholesterol (median 1.00 versus 1.11 mmol/L, p = 0.005), LDL cholesterol (median 2.90 versus 3.12 mmol/L, p = 0.039), and NIHSS score (median 1.0 versus 6.0, p < 0.001) were significantly higher in the mRS score >2 group than in the mRS score ≤2 group.There were no statistically significant differences between the two groups in terms of risk factors for cerebrovascular disease such as smoking, alcohol consumption, hypertension, diabetes mellitus, coronary artery disease, total cholesterol, and triglycerides.

| Association between the lymphocyte subsets and the severity of clinical outcomes
Patients were categorized into three subgroups based on the interval between stroke onset and hospitalization: the 1-3, 4-7, and 8-14 days groups.The proportions and counts of lymphocyte subsets were not statistically different with respect to the outcomes in the 4-7 and 8-14 days groups (Table 2).In the 1-3 days group, total T-cell percentage (mean 70.6 versus 67.0, p = 0.016), CD3 + Tcell count (median 1267 versus 1112 cells/μL, p = 0.002), and CD4 + T-cell count (median 760.0 versus 646.5 cells/μL, p = 0.002) were significantly higher in patients in the mRS score ≤2 group than in the mRS score >2 group.Additionally, the NK cell percentage (median 12 versus 16, p = 0.019) was lower in the mRS score ≤2 group than in the mRS score >2 group (Figure 1).

| Individualized prediction model
Combining the results of the multivariate logistic analyses in the 1-3 days group and using backward exclusion based on the AIC for variable selection, the final individualized prediction model for disease regression included sex (categorical variable), age (continuous   The optimal cutoff point was 0.237, with a sensitivity of 75% and a specificity of 81.3%.The calibration curve indicated that the model had reliable predictive accuracy.The Hosmer-Lemeshow test yielded p = 0.992, implying that the model was appropriately calibrated.The DCA curve reflected a relatively favorable net clinical benefit (Figure 3).

| DISCUSS ION
The objective of this study was to elucidate the link between peripheral blood lymphocyte subsets and prognosis in patients with AIS.
Prior research involving animal models has revealed that infarct size is reduced in mice lacking T cells, suggesting that T cell invasion into the brain may have deleterious effects. 17,18However, in our current study, we observed an elevated percentage of circulating T cells and increased counts of CD3 + and CD4 + T-cells in patients exhibiting favorable prognostic outcomes, consistent with findings from several preceding clinical trials. 19,20This can be attributed to multiple underlying mechanisms.
It is well known that in instances of ischemic stroke, neuroinflammation begins within minutes of the onset of ischemia and persists for several days.2][23] During this process, microglia in the brain activate CD4 + T cells, prompting their differentiation into either Th type 1 (Th1) cells, which secrete proinflammatory factors, or Th type 2 (Th2) cells, which release anti-inflammatory factors. 24perimental studies in mice have demonstrated an increased differentiation of the immune response toward the Th2-type following the acute phase of a cerebrovascular event. 25Therefore, we hypothesized that the elevated ratio of Th2 cells relative to Th1 cells results in increased release of anti-inflammatory factors, potentially playing a protective role in neural recovery and contributing to improved patient outcomes.It has been demonstrated that IL-4 plays a critical role in the differentiation of T cells into Th2 cells. 26,27Thus, whether IL-4 can be targeted as an intervention to mitigate neuroinflammation by balancing Th1 and Th2 cells warrants further exploration.
Existing evidence indicates that following ischemia, there is a notable upregulation in gene expression of TNFα, IFNγ, and IL-1β in mice deficient in regulatory T (Treg) cells.Additionally, antagonizing both TNFα and IFNγ has been shown to significantly decrease infarct size. 28Therefore, we hypothesized that the protective role of T cells after AIS is associated with a specific T cell subset, the Treg cells.Early Tregs achieve protective immunomodulation mainly through the secretion of IL-10. 29Moreover, inflammatory mediators may exert beneficial effects on stroke recovery.

Activated intrinsic immune cells like astrocytes not only release
damaging proinflammatory factors into the brain but also upregulate protective cytokines such as TGFβ, IL-33, and IL-2.These cytokines can bind to receptors within the CNS and corresponding receptors outside the CNS, thereby facilitating the development of Treg cells in the peripheral blood and enhancing their protective effects. 28,30,31 addition to inducing neuroinflammation following an ischemic stroke, another immune cascade response known as stroke-induced immunosuppression is triggered.Cytokines and inflammatory cells produced in the brain traverse the blood-brain barrier into the bloodstream, activating the peripheral immune system through the sympathetic nervous system and the hypothalamus-pituitary-adrenal axis.
3][34] However, glucocorticoids, the end product of the hypothalamus-pituitary-adrenal axis, despite their immunosuppressive effects, also stimulate the production of anti-inflammatory cytokines such as IL-10.They facilitate the proportional shift in the balance from Th1 cells to Th2 cells and thereby mitigate neuroinflammation, promoting neurological recovery. 35,36Therefore, we posit that the higher proportion of peripheral blood lymphocytes observed in patients with favorable prognoses may be linked to this mechanism, suggesting a promising avenue for future investigation.
This observational cohort study utilized prospectively collected data.Patients with AIS who visited the First Hospital of Jilin University stroke center between March and June 2023 were selected.Exclusion criteria included: (1) suffering from other serious systemic diseases such as autoimmune disorders, (2) acute infections, and (3) neurological deficits resulting from trauma or malignancy.Furthermore, clinical prognosis was evaluated utilizing the mRS score.A telephone follow-up was conducted 90 days post-stroke to assess the extent of neurological impairment using the mRS score.Typically, a mRS score of ≤2 was indicative of a favorable prognosis, reflecting a minimal neurological deficit, whereas a mRS score >2 was associated with a poor prognosis.This study was granted by the Ethics Committee of the First Hospital of Jilin University (22k047-003).
Data were obtained on demographic and clinical characteristics (age, sex, previous stroke, diabetes, hypertension, coronary artery disease, smoking and alcohol consumption, antihypertensive, hypoglycemic, and antiplatelet agents), laboratory tests [levels of total cholesterol, triglycerides, homocysteine, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol], the TOAST (Trial of Org 10,172 in Acute Stroke Treatment) subtype, and stroke severity as measured by the National Institutes of Health Stroke Scale (NIHSS) score on admission.Stroke severity was classified as mild (NIHSS score ≤4) and moderately severe (NIHSS score >4) according to the scale.Smoking was considered to be the daily use of at least one cigarette for a consecutive year.Alcohol consumption was characterized by the intake of one or more drinks per day over the past year.Hypertension was identified by either a recorded history or a clinical diagnosis established during the hospital stay.Diabetes was defined similarly by either a documented history or a hospital diagnosis.

F I G U R E 1
Violin plots of lymphocyte subset distributions that were significantly different between the different prognostic groups in the 1-3 days group.*p < 0.05 and **p < 0.01 by the Mann-Whitney U test or the Student t test.TA B L E 3 The baseline clinical characteristics of the patients in the AIS 1-3 days group.

TA B L E 4 F I G U R E 2
Abbreviations: CI, confidence interval; OR, odds ratio.

Furthermore, we developed 5 |
an individualized predictive model to predict adverse outcomes, with the model including age, sex, F I G U R E 3 ROC curves, calibration curve, and DCA of the nomogram model to predict outcome.ROC (left), calibration curve (middle), and DCA (right).In detail, the model's discrimination is assessed using ROC analysis.The dashed line in the calibration curves with bootstraps of 1000 resamples represents the ideal reference line, and the green vertical line represents the 95% CI as measured by Hosmer-Lemeshow analysis.The calibration curves show that there is good agreement between the model predictions (x-axis) and the actual observations (y-axis).In DCA, the x-axis denotes the risk threshold for unfavorable outcomes, while the y-axis represents the net benefit across various thresholds.A more distant curve signifies a higher net benefit.The black line represents the scenario where all patients have a poor prognosis, and the gray dotted line indicates that no patients have a poor prognosis.The other line shows the net benefit as predicted by the model.DCA, decision curve analysis; ROC, receiver operating characteristic curve.baseline NIHSS score, and HDL and CD4 + T-cell count.The metrics demonstrated that our model exhibited robust performance.Therefore, we conclude that the model based on CD4 + T-cell count has a good predictive value for patient prognosis.Although we initially explored possible factors that may influence and improve the prognosis of patients with stroke, our study had several limitations.First, this was an observational cohort study from a single-center hospital.Second, the dynamics of lymphocyte subsets throughout the stroke process were not adequately captured because each patient represented a single data point rather than multiple samples.In addition, in this study, toast typing was performed with a small number of patients with cardioembolic stroke, and therefore this type of data was combined with patients with other stroke types in order to obtain more reliable results from the available data.We plan to expand the sample size in future studies.This will allow us to more accurately analyze and present the characteristics and impact of cardioembolic stroke.Finally, extensive and long-term prospective clinical studies are necessary to better understand the connection between peripheral lymphocyte subsets and stroke prognosis.Exploring biomarkers for long-term prognosis could reveal new immunotherapeutic targets for ischemic stroke.CON CLUS ION We found that total T-cell percentage, CD3 + T-cell, and CD4 + T-cell counts were prognostically relevant variables in patients with AIS.Furthermore, a prognosis model based on CD4 + T-cell count showed good accuracy and potential for predicting disease outcomes.